| SMAP卫星海表盐度产品的检验与校正 |
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| 作者姓名： | 秦思思 王辉 朱江 万莉颖 张宇 王昊运 |
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| 作者单位： | National Meteorological Center, Beijing 100081, China;Numerical Weather Prediction Center of China Meteorological Administration, Beijing 100081, China,Key Laboratory of Research on Marine Hazards Forecasting, National Marine Environmental Forecasting Center, Beijing 100081, China,International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China;University of the Chinese Academy of Sciences, Beijing 100049, China,Key Laboratory of Research on Marine Hazards Forecasting, National Marine Environmental Forecasting Center, Beijing 100081, China,Key Laboratory of Research on Marine Hazards Forecasting, National Marine Environmental Forecasting Center, Beijing 100081, China,Key Laboratory of Research on Marine Hazards Forecasting, National Marine Environmental Forecasting Center, Beijing 100081, China;University of the Chinese Academy of Sciences, Beijing 100049, China |
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| 基金项目： | The National Key Research and Development Program of China under contract Nos 2016YFC1401409 and 2016YFC1401704; the National Natural Science Foundation of China under contract Nos 41506031 and 41606029. |
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| 摘 要： | In this study, sea surface salinity(SSS) Level 3(L3) daily product derived from soil moisture active passive(SMAP)during the year 2016, was validated and compared with SSS daily products derived from soil Moisture and ocean salinity(SMOS) and in-situ measurements. Generally, the root mean square error(RMSE) of the daily SSS products is larger along the coastal areas and at high latitudes and is smaller in the tropical regions and open oceans. Comparisons between the two types of daily satellite SSS product revealed that the RMSE was higher in the daily SMOS product than in the SMAP, whereas the bias of the daily SMOS was observed to be less than that of the SMAP when compared with Argo floats data. In addition, the latitude-dependent bias and RMSE of the SMAP SSS were found to be primarily influenced by the precipitation and the sea surface temperature(SST). Then, a regression analysis method which has adopted the precipitation and SST data was used to correct the larger bias of the daily SMAP product. It was confirmed that the corrected daily SMAP product could be used for assimilation in high-resolution forecast models, due to the fact that it was demonstrated to be unbiased and much closer to the in-situ measurements than the original uncorrected SMAP product.
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| 关 键 词： | sea surface salinity(SSS) SOIL MOISTURE active passive(SMAP) SOIL MOISTURE and ocean salinity(SMOS) VALIDATION CORRECTION |
| 收稿时间： | 2018-10-18 |
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